基于自适应光子发射的渐进式光子映射

通过对渐进式光子映射算法进行扩展,提出了一种基于自适应光子发射的渐进式光子映射算法.渐进式光子映射是一个多遍的全局光照算法,通过不断发射光子并渐进更新场景各点的光能估计能使其最终能收敛到无偏差的结果.由于渐进式光子映射完全使用密度估计来计算各点的光能,因此其收敛速度受光子分布影响较大.利用渐进式光子映射算法中固有的场景统计信息以及其多遍的特点,设计了一个自适应的光子发射策略,使得发射的光子能更多的分布在对最终绘制有效的区域,提高了原算法的绘制效率.     

光子映射在CUDA中的研究与实现

通过修改光子映射算法的实现过程,使得该算法能够通过CUDA完全运行在最新的GPU上,从而能够充分利用GPU强大的并行计算能力,加速光子映射的实现。光子映射在CUDA中的实现主要通过两个方面来完成：构建光子图和估计辐射能。同时为了提高对光子图中的光子信息的查找速度,采用了kd-tree结构来存储光子信息,使得可以通过KNN（K-Nearest Neighbor）快速搜索光子图。在所测试环境中,渲染速度是CPU中的近1O倍。     

基于GPU的光子映射并行化算法

针对串行情况下光子映射算法速度慢的问题,对光子映射算法并行化进行可行性分析,充分利用图像处理器(GPU)的统一设备计算架构(CUDA)的并行和计算能力,实现光子映射算法的并行化。同时针对算法中光子发射追踪阶段生成GPU线程数与光子数相同的方法的不足以及平均分配方法所造成的资源浪费等,提出线程之间协同工作的方法并采用动态平衡处理,使光子渲染速度提升了将近一倍。实验结果证明了多线程间协同工作及动态平衡相结合方法的有效性。     

基于CUDA的光线追踪优化算法研究与实现

在三维场景仿真过程中,为了实现真实的光影效果,通常采用光线追踪法对场景进行渲染。光线追踪算法的核心过程是光线与场景中的片元进行相交测试,而对于一个复杂的场景,该过程计算量非常大。为了改善光线追踪算法的计算速度问题,实现一种基于CUDA(Compute Unified Device Architecture)的光线追踪算法。该算法利用GPU的并行处理能力同时结合KD-Tree加速相交测试过程,最终提高仿真场景的渲染速度。通过实验表明,该算法的KD-Tree创建性能相比传统方法提升约20%,光线追踪性能提升约6倍。     

基于WEB的VRML交互式光线追踪渲染

本文采用Java语言编制了一个Applet程序支持基于WEB的VRML2．0观察器。用户可以使用任何操作系统的浏览器来运行该程序，进行VRML文件的查看。该观察器采用了光线追踪算法对场景进行交互实时渲染，可以获得很好的效果。该算法对传统光线追踪算法作了适当改进以适用于交互式渲染，并采用包围盒和空间划分树(k—d树)等措施来加快渲染的速度。     

基于栅格的全局光子图重建

基于光子图的光子映射算法能产生高质量的照片级图像。对于光照复杂的 场景,光子图需要存储大量光子以提高生成图像的质量,这不仅占用大量的内存空间,而且 光照估计的时间长。论文提出基于栅格的全局光子图重建的算法,即在光子包围盒被栅格化 后,其非空栅格中一定比例的光子被用来重建新的光子图,并保证重建前后栅格内光子能量 和守恒,这使得重建前后光子图的光照估计的效果相近。通过增加特定栅格中的重建光子数 目,能有效减少由几何偏差引起的光照估计误差,增强直接聚焦（焦散）和间接聚焦光照的 绘制效果;并使用简单方法检测生成图像中少量噪声,增加少量采样即可有效减少相应的噪 声。全局光子图重建算法的计算成本低,并保持生成图像的视觉独立性。     

重要度驱动的自适应Projection Map在光子图中的应用

在全局光照算法中,光子图算法是一种与视点无关的物空间辐射度近似计算方法,提出了一种基于重要度驱动采样的自适应Projection map算法,利用它可以在光子图算法中提高光子发射的有效性和准确性,加快渲染速度并取得更好的图像质量.实验表明,该算法能够有效地减少光源发射光子的次数,提高光子的命中率,具有相当的应用价值.     

基于光子映射的辐照度缓存算法

提出了一种全局光照计算方法,结合了两个知名的技术,光子映射和辐照度缓存.光子映射具有视点无关的优势,辐照度缓存可以快速计算间接光照,但后者是视点相关的,为了使光照缓存记录覆盖整个场景,辐照度缓存算法需要手动设置很多相机.利用这两种技术的各自优势,通过光子图来计算改进后的视点无关的辐照度缓存算法,实现了快速而准确的全局光...     

基于光线追踪的全局光照及降噪处理研究

传统的路径追踪算法能够有效地追踪光线的运动轨迹,从而在屏幕上呈现出真实的渲染效果,但传统的光线追踪算法只能够追踪镜面反射或规则的折射光,追踪漫反射光消耗太大,效率低下。基于蒙特卡洛概率方法的光线追踪能够从统计意义上很好地实现物体间漫反射的光照效果,极大地解决了传统光线追踪的缺陷和效率问题,然而只有当采样数为无限大时,蒙特卡洛方法才是无误差的。为了提升渲染性能和质量,尽可能缩小误差,提出了一种根据颜色采样分布进行降噪处理的优化方法,该方法可以减少采样数,通过后期处理来去除噪声。通过在自研图形引擎中渲染虚拟场景对比实验发现,根据颜色采样分布进行降噪处理的方法能够实现较好的渲染及降噪效果,提高整个算法的性能以及画面表现。     

基于物理的分布并行光线追踪算法

基于物理的光线追踪算法用于从三维场景模型生成逼真的二维图像,光线追踪渲染较为耗时,所以如何提高算法的效率成为研究热点。针对斯坦福大学经典的多线程光线追踪引擎--PBRT,考虑任务划分粒度和负载均衡等因素,基于两级任务划分体系,提出了动态自适应分布式并行光线追踪算法。实验中在保证高质量图像生成的前提下,使用80个CPU核时,改进算法比PBRT原算法获得了近乎线性的加速比。实验结果表明改进算法具有良好的效率和扩展性,能够有效地用于光线追踪成像,提高光线追踪成像效率。     

The Beam Radiance Estimate for Volumetric Photon Mapping

We present a new method for efficiently simulating the scattering of light within participating media. Using a theoretical reformulation of volumetric photon mapping, we develop a novel photon gathering technique for participating media. Traditional volumetric photon mapping samples the in‐scattered radiance at numerous points along the length of a single ray by performing costly range queries within the photon map. Our technique replaces these multiple point‐queries with a single beam‐query, which explicitly gathers all photons along the length of an entire ray. These photons are used to estimate the accumulated in‐scattered radiance arriving from a particular direction and need to be gathered only once per ray. Our method handles both fixed and adaptive kernels, is faster than regular volumetric photon mapping, and produces images with less noise.     

Mixing Monte Carlo and progressive rendering for improved global illumination

In this paper, we seek to eliminate the noise caused by caustic paths during progressive Monte Carlo path tracing. We employ a filtering strategy over path space, handling each subspace using specialized derivations of path tracing and progressive photon mapping. Evaluating diffuse paths with path tracing allows the use of sample stratification over both pixels and the image as a whole, whilst sharp detailed caustics are produced using progressive photon mapping. This is an efficient, low noise progressive algorithm with vanishing bias combining the advantages of both Monte Carlo methods, and particle tracing.     

The photon pipeline revisited

With the development of real-time ray tracing in recent years, it is now very interesting to ask if real-time performance can be achieved for high-quality rendering algorithms based on ray tracing. In this paper, we propose a pipelined architecture to implement reverse photon mapping. Our architecture can use real-time ray tracing to generate photon points and camera points, so the main challenge is how to implement the gathering phase that computes the final image. Traditionally, the gathering phase of photon mapping has only allowed coarse-grain parallelism, and this situation has been a source of inefficiency, cache thrashing, and limited throughput. To avail fine-grain pipelining and data parallelism, we arrange computations so that photons can be processed independently, similar to the way that triangles are efficiently processed in traditional real-time graphics hardware. We employ several techniques to improve cache behavior and to reduce communication overhead. Simulations show that the bandwidth requirements of this architecture are within the capacity of current and future hardware, and this suggests that photon mapping may be a good choice for real-time performance in the future.     

Adaptive Caustic Maps Using Deferred Shading

Caustic maps provide an interactive image-space method to render caustics, the focusing of light via reflection and refraction. Unfortunately, caustic mapping suffers problems similar to shadow mapping: aliasing from poor sampling and map projection as well as temporal incoherency from frame-to-frame sampling variations. To reduce these problems, researchers have suggested methods ranging from caustic blurring to building a multiresolution caustic map. Yet these all require a fixed photon sampling, precluding the use of importance-based photon densities. This paper introduces adaptive caustic maps. Instead of densely sampling photons via a rasterization pass, we adaptively emit photons using a deferred shading pass. We describe deferred rendering for refractive surfaces, which speeds rendering of refractive geometry up to 25% and with adaptive sampling speeds caustic rendering up to 200%. These benefits are particularly noticable for complex geometry or using millions of photons. While developed for a GPU rasterizer, adaptive caustic map creation can be performed by any renderer that individually traces photons, e.g., a GPU ray tracer.     

Interactive Rendering of Non‐Constant,Refractive Media Using the Ray Equations of Gradient‐Index Optics

Existing algorithms can efficiently render refractive objects of constant refractive index. For a medium with a continuously varying index of refraction, most algorithms use the ray equation of geometric optics to compute piecewise‐linear approximations of the non‐linear rays. By assuming a constant refractive index within each tracing step, these methods often need a large number of small steps to generate satisfactory images. In this paper, we present a new approach for tracing non‐constant, refractive media based on the ray equations of gradient‐index optics. We show that in a medium of constant index gradient, the ray equation has a closed‐form solution, and the intersection point between a ray and the medium boundaries can be efficiently computed using the bisection method. For general non‐constant media, we model the refractive index as a piecewise‐linear function and render the refraction by tracing the tetrahedron‐based representation of the media. Our algorithm can be easily combined with existing rendering algorithms such as photon mapping to generate complex refractive caustics at interactive frame rates. We also derive analytic ray formulations for tracing mirages – a special gradient‐index optical phenomenon.     

Hierarchical Photon Mapping

Photon mapping is an efficient method for producing high-quality, photorealistic images with full global illumination. In this paper we present a more accurate and efficient approach to final gathering using the photon map based upon hierarchical evaluation of the photons over each surface. We use the footprint of each gather ray to calculate the irradiance estimate area rather than deriving it from the local photon density. We then describe an efficient method for computing the irradiance from the photon map given an arbitrary estimate area. Finally, we demonstrate how the technique may be used to reduce variance and increase efficiency when sampling diffuse and glossy-specular BRDFs.     

Diffusion Based Photon Mapping

Density estimation employed in multi‐pass global illumination algorithms give cause to a trade‐off problem between bias and noise. The problem is seen most evident as blurring of strong illumination features. In particular, this blurring erodes fine structures and sharp lines prominent in caustics. To address this problem, we introduce a photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way, we preserve important illumination features, while eliminating noise. We demonstrate the applicability of our algorithm through a series of tests. In the tests, we evaluate the visual and computational performance of our algorithm comparing it to existing popular algorithms.     

Efficient Caustic Rendering with Lightweight Photon Mapping

Robust and efficient rendering of complex lighting effects, such as caustics, remains a challenging task. While algorithms like vertex connection and merging can render such effects robustly, their significant overhead over a simple path tracer is not always justified and – as we show in this paper ‐ also not necessary. In current rendering solutions, caustics often require the user to enable a specialized algorithm, usually a photon mapper, and hand‐tune its parameters. But even with carefully chosen parameters, photon mapping may still trace many photons that the path tracer could sample well enough, or, even worse, that are not visible at all. Our goal is robust, yet lightweight, caustics rendering. To that end, we propose a technique to identify and focus computation on the photon paths that offer significant variance reduction over samples from a path tracer. We apply this technique in a rendering solution combining path tracing and photon mapping. The photon emission is automatically guided towards regions where the photons are useful, i.e., provide substantial variance reduction for the currently rendered image. Our method achieves better photon densities with fewer light paths (and thus photons) than emission guiding approaches based on visual importance. In addition, we automatically determine an appropriate number of photons for a given scene, and the algorithm gracefully degenerates to pure path tracing for scenes that do not benefit from photon mapping.